Accuracy in fixing ship’s positions by camera survey of bearings

The paper presents the results of research on the possibilities of fixing ship position coordinates based on results of surveying bearings on navigational marks with the use of the CCD camera. Accuracy of the determination of ship position coordinates, expressed in terms of the mean error, was assumed to be the basic criterion of this estimation. The first part of the paper describes the method of the determination of the resolution and the mean error of the angle measurement, taken with a camera, and also the method of the determination of the mean error of position coordinates when two or more bearings were measured. There have been defined three software applications assigned for the development of navigational sea charts with accuracy areas mapped on. The second part contains the results of studying accuracy in fixing ship position coordinates, carried out in the Gulf of Gdansk, with the use of bearings taken obtained with the Rolleiflex and Sony cameras. The results are presented in a form of diagrams of the mean error of angle measurement, also in the form of navigational charts with accuracy fields mapped on. In the final part, basing on results obtained, the applicability of CCD cameras in automation of coastal navigation performance process is discussed.

[1]  Peter Stone,et al.  Selective Visual Attention for Object Detection on a Legged Robot , 2006, RoboCup.

[2]  Gérard G. Medioni,et al.  3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[3]  Andrew J. Davison,et al.  Real-time simultaneous localisation and mapping with a single camera , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[4]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization, Mapping and Moving Object Tracking , 2007, Int. J. Robotics Res..

[5]  Michel Dhome,et al.  Real Time Localization and 3D Reconstruction , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[6]  M. P. Bailey Performance of integrated air defense systems , 1990, 29th IEEE Conference on Decision and Control.

[7]  Robert T. Collins,et al.  Autonomous river navigation , 2004, SPIE Optics East.

[8]  Selim Benhimane,et al.  A new approach to vision-based robot control with omni-directional cameras , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[9]  Wolfram Burgard,et al.  Exploration with active loop-closing for FastSLAM , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[10]  José Santos-Victor,et al.  Experiments in Visual-Based Navigation with an Omnidirectional Camera , 2001 .

[11]  Dominick Andrisani,et al.  Performance of Integrated Electro-Optical Navigation Systems , 2003 .

[12]  Peter Stone,et al.  Practical Vision-Based Monte Carlo Localization on a Legged Robot , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[13]  Sebastian Thrun,et al.  FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.

[14]  M. BiancoGiovanni,et al.  Real-time analysis of the robustness of the navigation strategy of a visually guided mobile robot , 2000 .

[15]  Antti Vehkaoja,et al.  Automatic recognition of sector light boundaries based on digital imaging , 2007 .